Lemma REF  reveals that one can train \(T\)  domain discriminators with weighted Wasserstein adversarial loss. When the source target distributions are identical, this loss recovers the conventional Wasserstein adversarial loss [1]}. In practice, we adopt a hybrid approach by linearly combining the explicit and implicit matching, in which empirical results show its effectiveness.
